2026
TWINFUZZ: Dual-Model Fuzzing for Robustness Generalization in Deep Learning
AAAI 2026technical
Deep learning (DL) models are increasingly deployed in safety-critical applications such as face recognition, autonomous driving, and medical diagnosis. Despite their impressive accuracy, they remain vulnerable to adversarial examples - subtle perturbations that can cause incorrect predictions, i.e.